Skill UI

OSS-Fuzz gives open-source teams free distributed infrastructure for continuous fuzz testing, letting you build Docker images, compile sanitizing fuzzers, run harnesses, and review coverage/bugs through the helper.py CLI instead of hosting your own servers.

Phoenix is an open-source observability platform for tracing, evaluating, and monitoring LLM applications; use it to debug prompts, run dataset evaluations, build experiment pipelines, and watch production inference in real time.

LaminDB is a Python-driven open-source framework for managing biological datasets, ensuring traceable, reproducible, FAIR data through lineage tracking, schema validation, ontology annotation, workflow integration, and lakehouse-style querying.

Self-hosted open-source alternative to NotebookLM for organizing research, ingesting diverse sources, generating AI notes, running context-aware chats, performing vector search, producing multi-speaker podcasts, and automating workflows via a REST API.

Qiskit is the world's leading open-source framework for building, optimizing, and executing quantum circuits. It provides comprehensive capabilities for quantum error mitigation, running algorithms on diverse hardware backends (including IBM Quantum and simulators), and supporting applications in chemistry and machine learning. Essential for researchers entering the quantum computing field.

A powerful tool designed to scaffold and generate production-ready MCP servers directly from OpenAPI specifications. It treats OpenAPI as the single source of truth, automatically converting API paths and operations into standardized tool definitions. Supports both Python and TypeScript implementations, ensuring schema consistency, robust validation, and safe versioning for exposing internal APIs to LLM agents and other services.

Attempts to expose an open-source context resource, but the current skill metadata only yields a 404 response, indicating the referenced content is unavailable or missing from the system.

Osint Evals provides a structured way to assess open-source intelligence collection and analysis workflows, helping security teams benchmark their OSINT tooling and methodologies against predefined scenarios.

SciPy provides open-source algorithms and utilities for scientific computing, including integration, optimization, statistics, and signal processing, enabling researchers and engineers to build reliable numerical applications.

This module adopts the persona, vocabulary, and critical pedagogical style of Yann LeCun. It provides deep insights into open-source technology, the concept of technological sovereignty, and the geopolitical incentives driving major AI companies (Meta, OpenAI, Google). It structures explanations using Socratic methods, grounding complex AI concepts in physical analogies.

This skill generates a comprehensive daily digest summarizing all critical pending items into a single summary. It aggregates stalled scheduling threads, unanswered emails, pending introductions/follow-ups, open Todoist tasks, and upcoming calendar events from multiple sources. It is essential for running a daily summary cron job or when the user requires a quick status check on their workload and commitments.

Automates indicator enrichment through OpenCTI connectors, pulling context from VirusTotal, Shodan, AbuseIPDB, GreyNoise, and similar sources to score, correlate, and prioritize STIX-based IOCs for analysts and infrastructure deployments.